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dc.contributor.authorChandra, D. Rakesh-
dc.contributor.authorKumari, M. Sailaja-
dc.contributor.authorSydulu, M.-
dc.date.accessioned2025-01-22T11:17:02Z-
dc.date.available2025-01-22T11:17:02Z-
dc.date.issued2013-
dc.identifier.citation10.1109/ICPEC.2013.6527734en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/2861-
dc.descriptionNITWen_US
dc.description.abstractThere are several forecasting methods available to estimate the uncertainty of the wind. Wind behavior is chaotic in nature. These forecasting methods are used to predict wind power generation capacity for the grid. With the introduction of smart grid has created enough space for integrating renewable (wind power) in to the grid. Several methods have been proposed by researchers to estimate the wind speed. In present days there is a lot of research is going on to estimate the wind speed by using mathematical, biologically inspired computing methods to minimize the prediction error. This paper presents a review of several forecasting techniques which are using presently. This paper will be helpful for the new researchers who are going to work in this area. This paper will also be helpful to the wind farm operators to know about the present wind estimation model capabilities and will give an idea to estimate the wind speed at their particular wind farms.en_US
dc.language.isoenen_US
dc.publisherProceedings of 2013 International Conference on Power, Energy and Control, ICPEC 2013en_US
dc.subjectWind forecasting;en_US
dc.subjectAuto Regressive Moving Average (ARMA)en_US
dc.titleA detailed literature review on wind forecastingen_US
dc.typeOtheren_US
Appears in Collections:Electrical Engineering

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